Can we replicate real human behaviour using artificial neural networks?

Autor: Georg Jäger, Daniel Reisinger
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Mathematical and Computer Modelling of Dynamical Systems, Vol 28, Iss 1, Pp 95-109 (2022)
Druh dokumentu: article
ISSN: 13873954
1744-5051
1387-3954
DOI: 10.1080/13873954.2022.2039717
Popis: Agent-based modelling is a powerful tool when simulating human systems, yet when human behaviour cannot be described by simple rules or maximizing one’s own profit, we quickly reach the limits of this methodology. Machine learning has the potential to bridge this gap by providing a link between what people observe and how they act in order to reach their goal. In this paper we use a framework for agent-based modelling that utilizes human values like fairness, conformity and altruism. Using this framework we simulate a public goods game and compare to experimental results. We can report good agreement between simulation and experiment and furthermore find that the presented framework outperforms strict reinforcement learning. Both the framework and the utility function are generic enough that they can be used for arbitrary systems, which makes this method a promising candidate for a foundation of a universal agent-based model.
Databáze: Directory of Open Access Journals
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje